An aggrandized solution is designed for the vehicles to reduce the total cost of distribution by which it can supply the goods to the customers with its known capacity can be named as a vehicle routing problem. In variable neighborhood search method, mainly an efficient vehicle routing can be achieved by calculating the distance matrix value based on the customer's location or the path where the customer's resides. The main objective of the paper is to reduce the total distance travelled to deliver the goods to the customers. The proposed algorithm is a hierarchy based enhanced agglomerative clustering algorithm technique which is used in the data mining scenario effectively. The proposed algorithm decreases the total distance assigning to each route and the important thing need to consider is that, this enhanced clustering algorithm can reduce the total distance when compared to the previously proposed variable neighborhood search method. V. Praveen | V. Hemalatha | M. Poovizhi "An Enhanced Agglomerative Clustering Algorithm for Solving Vehicle Routing Problem" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: https://www.ijtsrd.com/papers/ijtsrd4701.pdf


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    Title :

    An Enhanced Agglomerative Clustering Algorithm for Solving Vehicle Routing Problem


    Contributors:
    V. Praveen (author) / V. Hemalatha (author) / M. Poovizhi (author)

    Publication date :

    2017-10-04


    Remarks:

    oai:zenodo.org:3580249
    International Journal of Trend in Scientific Research and Development 1(6) 919-924



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




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